%0 Journal Article
%T Multiple Outliers Detection Procedures in Linear Regression
%A Robiah Adnan
%A Mohd Nor Mohamad
%A Halim Setan
%J Matematika
%D 2003
%I Universiti Teknologi Malaysia
%X This paper describes a procedure for identifying multiple outliers in linear regression. This procedure uses a robust fit which is the least of trimmed of squares (LTS) and the single linkage clustering method to obtain the potential outliers. Then multiple-case diagnostics are used to obtain the outliers from these potential outliers. The performance of this procedure is also compared to Serbert¡¯s method. Monte Carlo simulations are used in determining which procedure performed best in all of the linear regression scenarios.
%K Multiple outliers
%K linear regression
%K robust fit
%K Least trimmed of squares
%K single linkage.
%U http://www.fs.utm.my/matematika/images/stories/matematika/200319105.pdf